The document outlines various definitions and dimensions of quality, such as reliability, durability, performance, and aesthetics, emphasizing their importance in meeting customer expectations. It contrasts quality control and quality assurance processes, detailing the systematic approaches to monitoring product quality through inspections and administrative procedures. Additionally, the document explores statistical quality control and acceptance sampling, highlighting the concepts of defects, inspection plans, and the associated risks for both consumers and producers.

1. Quality
Control
By
Nitin G Shekapure

2. Your definition of quality?
• High price?
• Reliable?
• Attractive?
• Durable?
• Other?

3. Quality - a Definition
• “Fitness for use” – Joseph Juran
• “Conformance to requirements” – Philip Crosby
• Based on various factors: reliability, durability,
performance, usefulness, aesthetics, price, etc. -
Various
• “Meets customer requirements” – Various
• “Consistently meets or exceeds customer
expectations” – William Stevenson

4. Quality - a Definition
• “Consistently meets or exceeds customer
requirements” – David Bentley
 Emphasis on requirements
 Includes understanding of expectations
 Implies an agreement
• explicit or Implicit
• Concept: “Do it right the first time and every time”

5. The Characteristics of Quality
 Durability
 Serviceability
 Aesthetics
 Perceived Quality
 Performance
 Features
 Reliability
 Conformance

6. Performance
• Performance refers to a product's
primary operating characteristics.
• This dimension of quality involves measurable attributes, so
brands can usually be ranked objectively on individual aspects
of performance.
• Overall performance rankings, however, are more difficult to
develop, especially when they involve benefits that not every
consumer needs. Performance is often a source of conflict
between customers and suppliers, particularly when
deliverables are not adequately defined within specifications.

7. Features
• Features are additional characteristics that enhance the
appeal of the product or service to the user.
• Similar thinking can be applied to features, a second
dimensions of quality that is often a secondary aspects of
performance. Features are the "bells and whistles" of
products and services, those characteristics that supplement
their basic functioning.
• Examples include free drinks on a plane.
• The line separating primary performance characteristics from
secondary features is often difficult to draw

8. Reliability
• Reliability is the likelihood that a product will not fail within a specific time
period. This is a key element for users who need the product to work
without fail.
• This dimension reflects the probability of a product malfunctioning or
failing within a specified time period.
• Reliability normally becomes more important to consumers as downtime
and maintenance become more expensive.
• Reliability may be closely related to performance. For instance, a product
specification may define parameters for up-time, or acceptable failure
rates. Reliability is a major contributor to brand or company image, and is
considered a fundamental dimension of quality by most end-users.

9. Conformance
• The dimension of conformance depicts to what extent a product’s
design and operating characteristics meet established standards.
This dimension owes the most to the traditional approaches to
quality pioneered by experts like Juran.
• All products and services involve specifications of some sort. When
products are developed, these specifications are set and a target is
set, for instance the materials used or the dimension of the
product. Not only the target but also the tolerance (the range of
permitted deviation from the target) is defined.
• In service businesses, measures of conformance normally focus on
accuracy and timeliness and include counts of processing errors,
unanticipated delays and other frequent mistakes

10. Durability
• Durability measures the length of a product’s life. When the product
can be repaired, estimating durability is more complicated. The item
will be used until it is no longer economical to operate it. This
happens when the repair rate and the associated costs increase
significantly.
• Technically, durability can be defined as the amount of use one gets
from a product before it deteriorates. After so many hours of use,
the filament of a light bulb burns up and the bulb must be replaced.
Repair is impossible.
• In other cases, consumers must weigh the expected cost, in both
cost and personal inconvenience, of future repairs against the
investment and operating expenses of a newer, more reliable model.
• Durability, then, may be defined as the amount of use one gets from
a product before it breaks down and replacement is preferable to
continued repair.
• The durability and reliability are closely linked.

11. Serviceability
• Serviceability involves the consumer's ease of obtaining repair service.
• The responsiveness of service personnel and the reliability of service.
• Important attributes for serviceability dimension are: service warranty,
parts warranty, parts availability, number of reasonable distance to
dealer service centers, distance to service parts center-dealer, distance
to service parts center individual, length of wait for service
appointment, schedule of preventive maintenance, employees listen to
customers, information regarding repairs, courteous service centers,
repaired correctly first time, service time relative to other dealers,
warranty claims handled without argument, average repair cost/year,
extended warranty etc.

12. Aesthetics
• The aesthetic properties of a product contribute to a company's or
brand's identity.
• Faults or defects in a product that diminish its aesthetic properties,
even those that do not reduce or alter other dimensions of quality,
are often cause for rejection.
• Aesthetics refers to how the product looks, feels, sounds, tastes or
smells. It is clearly a matter of personal judgment and a reflection of
individual preference.
• Aesthetics also refers to the "outside" feel of the product.
• Not all people prefer "rich and full" flavor or even agree on what
that means. Companies therefore have to search for a niche. On this
dimension of quality, it is impossible to please everyone.

13. Perceived Quality
• Perception is not always reality. Consumers do not always have
complete information about a product's or service's attributes;
indirect measures may be their only basis for comparing brands.
• A product's durability for example, can seldom be observed directly;
it usually must be inferred from various tangible and intangible
aspects of the product. In such circumstances, images, advertising
and brand names-inferences about quality rather than the reality
itself-can be critical.
• Reputation is the primary stuff of perceived quality. Its power comes
from an unstated analogy: the quality of goods in a new product line
is similar to the quality of a company's established products.

14. Quality Control
Quality control, or QC for short, is a process by which entities
review the quality of all factors involved in production. This
approach places an emphasis on three aspects:
1. Elements such as controls, job management, defined and well
managed processes, performance and integrity criteria, and
identification of records
2. Competence, such as knowledge, skills, experience, and
qualifications
3. Soft elements, such as personnel, integrity, confidence,
organizational culture, motivation, team spirit, and quality
relationships.

15. Quality Control
Quality Control refers to the checks carried out on a product by
workers, during stages of its manufacture. These checks may
include, simply ensuring that components are positioned
correctly, or that they are the correct type and size. A final
quality check should include, testing the product to ensure it is
to the correct standard, before it is distributed to the retailer /
customer. A combination of visual checks and automated
checks (by sensors and computers) are usually carried out.

16. Quality Assurance
Quality Assurance is the term used by manufacturers,
to describe the ‘administrative system’ put in place, to
ensure that quality control (checks carried out by
workers on a product / component) can be carried out
effectively.
1. Quality Assurance should ensure that staff training,
administrative procedures and quality monitoring
of the product at various stages of manufacture, is
to the highest standard.
2. Customer surveys will be carried out to ensure
customer satisfaction, all part of quality assurance.

17. How do Quality Control and Quality Assurance differ?
Quality Assurance is the system of administrative
procedures, set up to ensure that effective quality
control on the production line can be carried out. This
includes the training of staff, so that they know how to
recognise substandard work / products.
Quality Control is, carrying out regular checks on the
production line, as a product is manufactured.
Substandard components / products are rejected,
ensuring that only products of the correct standard are
distributed to the customer / retailer.

18. There is a tendency for individual consultants and organizations to
name their own unique approaches to quality control—a few of these
have ended up in widespread use:
Terminology
Approximate
year of first use
Description
Statistical quality
control (SQC)
1930s
The application of statistical methods (specifically control charts
and acceptance sampling) to quality control.
Total quality control
(TQC)
1956
Popularized by Armand V. Feigenbaum in a Harvard Business
Review article and book of the same name. Stresses involvement
of departments in addition to production (e.g., accounting, design,
finance, human resources, marketing, purchasing, sales).
Statistical process
control (SPC)
1960s
The use of control charts to monitor an individual industrial
process and feed back performance to the operators responsible
for that process. Inspired by control systems.
Company-wide
quality control
(CWQC)
1968 Japanese-style total quality control
Total Quality
Management (TQM)
1985
Quality movement originating in the United States Department of
Defense that uses (in part) the techniques of statistical quality
control to drive continuous organizational improvement.
Six Sigma (6σ) 1986
Statistical quality control applied to business strategy.
Originated by Motorola.

19. Statistical Quality Control
Statistical Quality control (SQC) involves the statistical analysis
of the inspection data. Which is based on sampling and the
principle involved in normal curve.
There are two different ways of controlling the quality of the
product:
1. Through 100 % inspection, i.e., by inspecting each and item
that is produced.
2. Through sampling techniques or the use of statistical quality
control.

20. What is Sampling Inspection?
Sampling inspection is conducted to evaluate the quality of a
lot of product, through the careful examination of a small no. of
units of products drawn from the lot.
The purpose of sampling inspection is to
1. Interpret the specification
2. Measure the product
3. Compare 1 with 2
4. Modify the provision for tightened and reduced inspection.
5. Provide for the construction of one’s own sampling plans
6. Utilize experience gained during previous years to the
present version

21. What is Sampling Inspection?
The main purpose of sampling inspection or
acceptance sampling is to distinguish between good
lots and bad, and to classify the lots of product
according to their acceptability or non-acceptability
When an inspection has been made of all the items in
the lot, it is called 100% inspection.
When inspection is made of only a part of the lot. i.e.
on a sample, it is called sampling inspection

22. Advantage and disadvantage of sampling
100% inspection – some undesirable aspects
1. It is quite uneconomical
2. It is not possible in destructive test
3. It gives false assurance about the completeness of the
job inspection
4. It actually sorting and therefore, result in fatigue of
the inspectors
5. It may result in accepting some defective materials
due to fatigue of the inspectors
6. For the same reason it may result in rejecting some
satisfactory materials/products.
7. It is impracticable when the lot size is large.

23. Advantages of Sampling Inspection
1. Economical through less inspection lower no. of inspection
2. There is less damage during inspection
3. Where inspection involves destructive tests, use of sampling
technique is ‘inevitable’
4. Varying quality levels can be achieved by varying the sampling
procedure
5. It causes less fatigue to the inspectors
6. Exert more pressure on the supplier to improve quality.
Disadvantages of Sampling Inspection
1. There are risks of accepting ‘bad’ lot and rejecting the good lot
2. Some extra planning and documentation is necessary
3. The sample usually provides less information about the product
than the 100% inspection.

24. When to use acceptance sampling?
1) When testing is destructive.
2) When the cost of 100% inspection is high.
3) When 100% inspection is not technologically feasible or would
require so much calendar time and/or expenses.
4) When there are many items to be inspected and the
inspection error rate is high.
5) When the vendor has an excellent quality history, and some
reduction in inspection from 100% is desired.
6) When there are potentially serious product liability risks.

25. Terminology
Sampling Plan: A statement of the sampling procedure and rule
for making decision about the lot.
Sampling Inspection: Inspection in which only a portion of the lot
is inspected with view on making decision about accepting and
rejecting the lot with respect to certain characteristics
Lot: A collection of items which inspection will be performed.
Lot Size (N): Number of items in a lot
Sample: Group of items drawn from a lot for inspection
Sample Size (n): Number of items in the sample

26. Terminology
Critical Defect: A defect that would render (turn in to) an item
totally fit for use or could result in hazardous or unsafe conditions
for individuals using or maintaining the item such as hole at the
bottom of a test tube, leakage of electric current in an electric
appliance etc.
Major Defect: A defect, other than critical defect that could result
in failure or materially reduce the usability of the item of product
for its intended purposes such as missing thread of a fastener etc.
Minor Defect: Defects other than critical and major defects that
does not materially reduce the usability of the product for its
intended purpose.

27. Terminology
Defective: An item the quality of which does not meet the
requirement
Acceptance Number (a): The maximum allowable number of
defectives (or count of defects) in the samples for acceptance of
the lot.
Rejection Number (r): The minimum of defectives (or count of
defects) in the samples for rejection of the lot.
Acceptable Quality Level (AQL): The maximum percent defective
(or the number of defects per 100 items) that for the purpose of
sampling inspection, can be considered satisfactory as a process
average.

28. Terminology
Lot Tolerance Percent Defective (LTPD): The percentage or
defectives or the number of defects per 100 items in a lot that can
be tolerated in only a specific proportion of lots (which is
conventionally taken as 10 percent).
Average Outgoing Quality (AOQ): The average quality (that is,
the average percentage defectives or number of defects per 100
items) in the outgoing material when all rejected lots are
concerned and after the replacement of the defectives found.
(that is the maximum AOQ)

29. Sampling by attributes vs. sampling by variables
Attributes("go no-go" inspection)
• Defectives-product acceptability across range
• Defects-number of defects per unit
Variable (continuous measurement)
• Usually measured by mean and standard deviation

30. Commonly used Sampling Plans
Sampling scheme commonly use for attributes are
usually classified into four categories
1. Single Sampling Plan
2. Double Sampling Plan
3. Multiple Sampling Plan
4. Sequential Sampling Plan

31. Single-Sampling Plans for Attributes
A single sampling plan is defined by sample size, n, and the
acceptance number c. Say there are N total items in a lot.
Choose n of the items at random. If at least c of the items are
unacceptable, reject the lot.
N = lot size
n = sample size
c = acceptance number
d = observed number of defectives
The acceptance or rejection of the lot is based on the results
from a single sample - thus a single-sampling plan.

32. Single-Sampling Plans for Attributes
(n,c)
Accept the lot
Reject the lot
Sn≦C
Sn>C
(N, d)
Total number ：N
The proportion of defects :d
Where Sn is the number of the actual defects in the sample.

33. Double-Sampling Plans for Attributes
(n,c1 ,r1)
Acc the lot
Reject the lot
Sn1≦c1
Sn1>c1
(n1+n2, c2)
c1<Sn1<r1
Acc the lot
Reject the lot
S(n1+n2) ≦c2
S(n1+n2) >c2
(N, d)

34. Double-Sampling Plans for Attributes

35. Multiple-Sampling Plans for Attributes
……
(n,d)
Acc the lot
Reject the lot
Sn1≦c1
Sn1>c1
(n1+n2)
c1<Sn1<r1
Acc the lot
Reject the lot
S(n1+n2)<r2
S(n1+n2)≧r2
(n1+n2+n3)
c2<S(n1+n2)<r2

36. Sequential-Sampling Plans for Attributes

37. Risk
 Acceptable Quality Level (AQL)
 Max. acceptable percentage of defectives agreed by the
producer and user.
 a (Producer’s risk)
 The probability of rejecting a good lot.
 Lot Tolerance Percent Defective (LTPD)
 Percentage of defectives that defines consumer’s
rejection point.
  (Consumer’s risk)
 The probability of accepting a bad lot.

38. Operating Characteristic Curve
n = 99
c = 4
AQL LTPD
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1 2 3 4 5 6 7 8 9 10 11 12
Percent defective
Probabilityofacceptance
 =.17
(consumer’s risk)
a = .05 (producer’s risk)

39. Operating Characteristic (OC) Curve
1. OC curves are graphs which show the probability of
accepting a lot given various proportions of defects
in the lot
2. X-axis shows % of items that are defective in a lot-
“lot quality”
3. Y-axis shows the probability or chance of accepting a
lot
4. As proportion of defects increases, the chance of
accepting lot decreases
5. Example: 90% chance of accepting a lot with 5%
defectives; 10% chance of accepting a lot with 24%
defectives

40. Operating Characteristic (OC) Curve

41. Operating Characteristic (OC) Curve

42. Consumer’s Risk (α) is the chance of accepting a lot
that contains a greater number of defects than the
LTPD limit; Type II error
This is the probability, for a given (n,c) sampling plan,
of accepting a lot with a defect level equal to the
LTPD. The consumer suffers when this occurs, because
a lot with unacceptable quality was accepted. The
symbol β is commonly used for the Type II error and
typical values range from 0.2 to 0.01.
Consumer’s Risk

43. Producer’s risk (β) is the chance a lot containing an
acceptable quality level will be rejected; Type I error
This is the probability, for a given (n,c) sampling plan,
of rejecting a lot that has a defect level equal to the
AQL. The producer suffers when this occurs, because a
lot with acceptable quality was rejected. The symbol α
is commonly used for the Type I error and typical
values for range from 0.2 to 0.01.
Producer’s risk